Responsibilities
- Develop new algorithms to understand the scene around the robot, and how that scene would evolve through time
- Build multi-modal foundation models for on-vehicle and offline applications
- Develop new algorithms to apply generative AI to simulation to improve the realism of our offline validation systems
- Leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field
- Provide technical mentorship to the broader group of ML developers at Zoox
- Collaborate with engineers on Prediction, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments
Qualifications
- BS, MS, or PhD degree in computer science or related field
- Experience with training and deploying Deep Learning models on sensor data-Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
- Experience with modern computer vision techniques
- Strong mathematical skills and understanding of probabilistic techniques
- Fluency in C++ or Fluency in Python with a basic understanding of C++
- Extensive experience with programming and algorithm design-Strong mathematics skills
Bonus Qualifications
- Publications in your field (CVPR, ICCV, RSS, ICRA preferred)
- Experience with autonomous robots
- Experience with realtime sensor fusion (e.g. LiDAR, camera, radar)
- Experience with novel pipelines and architectures for convolutional neural nets
- Experience with 3D data and representations (pointclouds, meshes, etc.)
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